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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A Framework for Identifying Building Energy Models of Localized Utility Service Areas Using Smart Meter Data

Bottom-up load modeling of buildings offers a versatile approach to simulating baseline demand and scenarios of future technology evolution and adoption at the individual building level. This capability is essential to understanding how future load shapes may change with the adoption of electric equipment and vehicles, particularly as it relates to grid planning and infrastructure investments. Traditionally, grid planning techniques have used historical load data to predict future load and infrastructure needs. However, with the anticipated rise in adoption of electrification technologies such as heat pumps and electric vehicles, historical data become less reliable predictors of the future. By employing ResStock, a high-fidelity building stock modeling tool, we can fine-tune electrification scenarios and aggregate models to represent varying geographic resolutions of the grid system, while considering the underlying features of homes. This may enable a more accurate and responsive approach to anticipate and plan for the evolving landscape of energy demands. We present a new framework that leverages building stock energy modeling to identify building models that align with the load shapes and housing attributes of buildings with AMI data. This approach applies two model layers: (1) a classification step that identifies the presence of air conditioning, electric heating, and electric water heating, and (2) an optimization routine that identifies building energy models aligning with load profile data from advanced metering infrastructure meters. This report demonstrates one approach to deploying this framework, and presents results for three test cases that use both modeled and AMI data to assess performance. For a test case using AMI data in Fort Collins, Colorado, we observed a median monthly electricity load CV-RMSE of 16.6%, and a top ten daily heating and cooling median absolute percent error of 7.7% and 8.3%, respectively. For each AMI meter, we identify a set of potential energy models so that downstream use-cases can account for uncertainty driven by variability of baseline technologies and occupant behavior, which impact the response to electrification and energy efficiency scenarios. Our results indicate that ResStock has potential as a scalable solution for modeling residential energy demand at local grid resolutions. Its performance depends on location-specific factors, underlying building characteristics, and the level of aggregation, offering a path towards more precise and adaptive distribution grid planning for the evolving energy landscape.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

FERC Order No. 2222 and Considerations for Distributed Wind

The Federal Energy Regulatory Commission (FERC) issued Order No. 2222 in October 2020. The rule directs Regional Transmission Organizations and Independent System Operators (ISOs) to amend their tariffs and participation models to accommodate heterogeneous distributed energy resource (DER) aggregations in the wholesale energy markets that they operate, including capacity, energy, and ancillary service markets. The Commission issued the rule to better capture the benefits provided by DERs deployed in the United States, whose use has been expanding rapidly. The Commission defines DERs as “any resource located on the distribution system, any subsystem thereof or behind a customer meter,” including but not limited to “electric storage resources, distributed generation, demand response, energy efficiency, thermal storage, and electric vehicles and their supply equipment.” The rule aims to increase DER participation in wholesale markets by allowing the creation of DER aggregations, in which multiple DERs that are too small to meet minimum capacity requirements for wholesale markets individually would be able to participate in markets as a single unit. As of June 20, 2023, all ISOs have filed initial compliance plans and a number have begun implementation. Compliance dates range from 2024 to 2029, with Midcontinent ISO having the latest date of compliance proposed for 2029. Southwest Power Pool still has an outstanding date, having no final order yet from FERC, but a target date of the third quarter of calendar year 2025. The rule, which is technology agnostic and requires ISOs to create participation plans that accommodate different DERs, provides an opportunity for distributed wind market expansion. In addition, distributed wind can bring benefits to heterogenous DER aggregations. These benefits include resource diversity (i.e., a complementary generation profile to other types of distributed generation), its small footprint and ability to be co-located with load, and its potential to provide frequency response, voltage support, and black start services, among other ancillary services. This report provides a status update on FERC Order No. 2222, the current state of ISO compliance, and information relevant to the distributed wind industry as DER aggregators and other stakeholders expand their participation to wholesale energy markets.

17 WIND ENERGY↗
DOE OSTI2018

Privacy-Preserving Aggregation of Controllable Loads to Compensate Fluctuations in Solar Power

Cybersecurity and privacy are of the utmost importance for safe, reliable operation of the electric grid. It is well known that the increased connectivity/interoperability between all stakeholders (e.g., utilities, suppliers, and consumers) will enable personal information collection. Significant advanced metering infrastructure (AMI) deployment and demand response (DR) programs across the country, while enable enhanced automation, also generate energy data on individual consumers that can potentially be used for exploiting privacy. Inspired by existing works which consider DR, battery-based perturbation, and differential privacy noise adding, we novelly consider the aggregator (cluster) level privacy issue in the DR framework of solar photovoltaic (PV) generation following. Different from most of the existing works which mainly rely on the charging/discharging scheduling of rechargeable batteries, we utilize controllable building loads to serve as virtual storage devices to absorb a large portion of the PV genertaion while delicately keeping desired noisy terms to satisfy the differential privacy for the raw load profiles at the aggregator level. This not only ensures differential privacy, but also improves the DR efficiency in load following since part of the noisy signal in solar PV generation has been filtered out. In particular, a mixed integer quadratic optimization problem is formulated to optimally dispatch a population of on/off controllable loads to achieve this privacy-preserving DR service.

Dong, Jin↗
DOE OSTI2021

Decentralized Failure-Tolerant Optimization of Electric Vehicle Charging

We present a decentralized failure-tolerant algorithm for optimizing electric vehicle (EV) charging, using charging stations as computing agents. The algorithm is based on the alternating direction method of multipliers (ADMM) and it has the following features: (i) It handles capacity, peak demand, and ancillary services coupling constraints. (ii) It does not require a central agent collecting information and performing coordination (e.g. an aggregator), instead all agents exchange information and computations are carried out in a fully decentralized fashion. (iii) It can withstand the failure of any number of computing agents, as long as the remaining computing agents are in a connected communications network. We construct this algorithm by reformulating the optimal EV charging problem in a decomposable form, amenable to ADMM, and then developing efficient decentralized solution methods for the subproblems dealing with coupling constraints. We conduct numerical experiments on industry-scale synthetic EV charging datasets, with up to 1,152 charging stations, using a high performance computing cluster. The experiments demonstrate that the proposed algorithm can solve the optimal EV charging problem fast enough to permit the integration of EV charging with real-time electricity markets, even in the presence of failures.

42 ENGINEERING↗
DOE OSTI2023

Curb Allocation and Pick-Up Drop-Off Aggregation for a Shared Autonomous Vehicle Fleet

Advances in information technologies and vehicle automation have birthed new transportation services, including shared autonomous vehicles (SAVs). Shared autonomous vehicles are on-demand self-driving taxis, with flexible routes and schedules, able to replace personal vehicles for many trips in the near future. The siting and density of pick-up and drop-off (PUDO) points for SAVs, much like bus stops, can be key in planning SAV fleet operations, since PUDOs impact SAV demand, route choices, passenger wait times, and network congestion. Unlike traditional human-driven taxis and ride-hailing vehicles like Lyft and Uber, SAVs are unlikely to engage in quasi-legal procedures, like double parking or fire hydrant pick-ups. In congested settings, like central business districts (CBD) or airport curbs, SAVs and others will not be allowed to pick up and drop off passengers wherever they like. This paper uses an agent-based simulation to model the impact of different PUDO locations and densities in the Austin, Texas CBD, where land values are highest and curb spaces are coveted. In this paper 18 scenarios were tested, varying PUDO density, fleet size and fare price. The results show that for a given fare price and fleet size, PUDO spacing (e.g., one block vs. three blocks) has significant impact on ridership, vehicle-miles travelled, vehicle occupancy, and revenue. A good fleet size to serve the region’s 80 core square miles is 4000 SAVs, charging a $1 fare per mile of travel distance, and with PUDOs spaced three blocks of distance apart from each other in the CBD.

Hunter, Christian B.↗
DOE OSTI2024

Object-Oriented Controllable High-Resolution Residential Energy (OCHRE) (TM) Model

This presentation describes the OCHRE model as part of NREL's Powered By webinar series. OCHRE is a building energy modeling tool designed to model flexible loads in residential buildings. OCHRE includes detailed models and controls for flexible devices including HVAC equipment, water heaters, electric vehicles, solar PV, and batteries. It is designed to run in co-simulation with custom controllers, aggregators, and grid models.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Demand Response in Residential Energy Code: Technical Brief

As buildings account for over 75% of U.S. electricity use, effectively managing their loads can greatly facilitate the transition towards a clean, reliable grid. Grid-interactive efficient buildings (GEBs) combine efficiency and demand flexibility with smart technologies and communication to provide occupant comfort and productivity while serving the grid as a distributed energy resource (DER). In turn, GEBs can play a key role in ensuring access to an affordable, reliable, sustainable, and modern U.S. electric power system. Their national adoption could provide $\$$100-200 billion in U.S. electric power system cost savings over the next two decades. The associated reduction in CO 2 emissions is estimated at 6% per year by 2030 (DOE 2021). Building codes represent standard design practice in the construction industry and continually evolve to include advanced technologies and innovative practices. Historically, national model energy codes establish minimum efficiency requirements for new construction (ICC 2020). Expanding codes to support GEB capabilities is a pivotal step towards realizing demand flexibility in support of a clean grid by addressing capabilities to improve interoperability between smart building systems, the grid, and renewable energy resources. Realizing GEBs requires buildings with automated demand response (DR) capabilities that enable standardized communication with or control of, subject to explicit consumer consent, energy smart appliances or home energy management systems. This is achieved through direct or indirect (i.e., via an aggregator) communication between appliances and the electric grid. Energy codes can also support DR communication standardization and advance the deployment of building-integrated DERs such as energy storage, generation, and electric vehicles (EVs). Incorporating automated DR capabilities in energy codes provides many benefits to the consumers. Specifically, it aligns building electric load demand with intermittent renewable energy source availability, decreases peak load on the electric grid, allows buildings to respond to utility price signals, supports electrical network reliability and market growth of products and processes aligned with clean economic growth. The incorporation of DR into the model residential energy codes was considered for both the 2021 and 2024 International Energy Conservation Code (IECC) code development cycles. The approved DR measures in the 2021 cycle were removed in response to appeals (ICC 2020). Updated language was presented for consideration again for the 2024 IECC, where it was negotiated and again approved, and again removed in response to appeals (ICC 2024). This resulted in many sections, including sections on demand responsive controls, being moved to the credits options or an appendix as a voluntary application. This technical brief updates the proposed DR components such that they can be considered by states and local governments for direct incorporation into their codes, as well as for future IECC energy code development. The proposal refinements are intended to support consistency in approach and provide a degree of certainty for building owners, designers, contractors, manufacturers, and building and fire safety professionals. The scope of this technical brief includes three strategies for DR in residential buildings: 1) smart thermostats with demand-responsive control, 2) electric water heating incorporating demand-responsive controls and communication and 3) grid Integrated solar and energy storage systems.

2021 IECC↗
NASA NTRS1976

The economic impact of NASA R and D spending

The economic impact of R and D spending, particularly NASA R and D spending, on the U. S. economy was evaluated. The crux of the methodology and hence the results revolve around the fact that it was necessary to consider both the demand effects of increased spending and the supply effects of a higher rate of technological growth and a larger total productive capacity. The demand effects are primarily short-run in nature, while the supply effects do not begin to have a significant effect on aggregate economic activity until the fifth year after increased expenditures have taken place. The short-term economic impact of alternative levels of NASA expenditures for 1975 was first examined. The long-term economic impact of increased levels of NASA R and D spending over a sustained period was then evaluated.

Evans, M. K.↗
DOE OSTI2016

VOLTTRON-Based System for Providing Ancillary Services with Residential Building Loads

Ancillary services entail controlled modulation of building equipment to maintain a stable balance of generation and load in the power system. Ancillary services include frequency regulation and contingency reserves, whose acting time ranges from several seconds to several minutes. Many pilot studies have been implemented to use industrial loads to provide ancillary services, and some have explored services from commercial building loads or electric vehicle charging loads. Residential loads, such as space conditioning and water heating, represent a largely untapped resource for providing ancillary services. The residential building sector accounts for a significant fraction of the total electricity use in the United States. Many loads in residential buildings are flexible and could potentially be curtailed or shifted at the request of the grid. However, there are many barriers that prevent residential loads being widely used for ancillary services. One of the major technical barriers is the lack of communication capabilities between end-use devices and the grid. End-use devices need to be able to receive the automatic generation control (AGC) signal from the grid operator and supply certain types of telemetry to verify response. With the advance of consumer electronics, communication-enabled, or 'connected,' residential equipment has emerged to overcome the communication barrier. However, these end-use devices have introduced a new interoperability challenge due to the existence of numerous standards and communication protocols among different end devices. In this paper, we present a VOLTTRON-based system that overcomes these technical challenges and provides ancillary services with residential loads. VOLTTRON is an open-source control and sensing platform for building energy management, facilitating interoperability solutions for end devices. We have developed drivers to communicate and control different types of end devices through standard-based interfaces, manufacturer-provided application programming interfaces, and proprietary communication interfaces. We document the ability to manage nine appliances, using four different standards or proprietary communication methods. A hardware-in-the-loop test was performed in a laboratory environment where the loads of a laboratory home and a large number of simulated homes are controlled by an aggregator. Upon receipt of an AGC signal, the VOLTTRON home energy management system (HEMS) of the laboratory home adjusts the end-device controls based on the comfort criteria set by the end users and sends telemetry to the aggregator to verify response. The aggregator then sends the AGC signal to other simulated homes in attempts to match the utility request as closely as possible. Frequency regulation is generally considered a higher value service than other ancillary services but it is also more challenging due to the constraint of short response time. A frequency regulation use case has been implemented with the regulation signals sent every 10 seconds. Experimental results indicate that the VOLTTRON-controlled residential loads are able to be controlled with sufficient fidelity to enable an aggregator to meet frequency regulation requirements. Future work is warranted, such as understanding the impact of this type of control on equipment life, and market requirements needed to open up residential loads to ancillary service aggregators.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Local Communication in Populations of Thermostatically Controlled Loads

Thermostatically controlled loads (TCLs) have shown great potential for demand response (DR) in electric grid operations. However, it has been commonly seen that DR events using TCLs may cause load synchronization and unwanted oscillatory effects, especially in homogeneous populations. In an attempt to mitigate the negative impacts of DR events, a decentralized method is proposed that modifies each thermostat behavior based on the activity of a small number of nearby TCLs. This feedback introduces the possibility of instability in the aggregate behavior. A stability analysis is performed on a linearized model of the aggregate system and the results of that analysis compared to simulation results. The proposed modification of thermostat behavior results in fourfold reduction in the post-DR peak while suppressing ensuing oscillations at the expense of a modest increase in compressor cycling. Further, the linearized model also provides insight into the aggregate behavior of the population.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Isolation of a Cu–H Monomer Enabled by Remote Steric Substitution of a N-Heterocyclic Carbene Ligand: Stoichiometric Insertion and Catalytic Hydroboration of Internal Alkenes

Transient Cu–H monomers have long been invoked in the mechanisms of substrate insertion in Cu–H catalysis. Their role from Cu–H aggregates has been mostly inferred since ligands to stabilize these monomeric intermediates for systematic studies remain limited. Within the last decade, new sterically demanding N-heterocyclic carbene (NHC) ligands have led to isolable Cu–H dimers and, in some cases, spectroscopic characterization of Cu–H monomers in solution. In this work, we report an NHC ligand, IPr*R, containing para R groups of CHPh 2 and CPh 3 on the ligand periphery for the isolation of a Cu–H monomer for insertion of internal alkenes. This reactivity has not been reported for (NHC)CuH complexes despite their common application in Cu–H-catalyzed hydrofunctionalization. Changing from CHPh 2 to CPh 3 impacts the relative concentration of Cu–H monomers, rate of alkene insertion, and reaction of a trisubstituted internal alkene. Specifically, for R = CPh 3 , monomeric (IPr*CPh 3 )CuH was isolated and provided >95% monomer (10 mM in C 6 D 6 ). In contrast, for R = CHPh 2 , solutions of [(IPr*CHPh 2 )CuH] 2 are 80% dimer and 20% (IPr*CHPh 2 )CuH monomer at 25 °C based on 1 H, 13 C, and 1 H– 13 C HMBC NMR spectroscopy. Quantitative 1 H NMR kinetic studies on cyclopentene insertion into Cu–H complexes to form the corresponding Cu–cyclopentyl complexes demonstrate a strong dependence on the rate of insertion and concentration of the Cu–H monomer. Only (IPr*CPh 3 )CuH, which has a high monomer concentration, underwent regioselective insertion of a trisubstituted internal alkene, 1-methylcyclopentene, to give (IPr*CPh 3 )Cu(2-methylcyclopentyl), which has been crystallographically characterized. We also demonstrated that (IPr*CPh 3 )CuH catalyzes the hydroboration of cyclopentene and methylcyclopentene with pinacolborane.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Influence of Groundwater Extraction Costs and Resource Depletion Limits on Simulated Global Nonrenewable Water Withdrawals Over the Twenty‐First Century

Abstract Future rates of global groundwater depletion will depend on the economic and environmental viability of extracting water from increasingly stressed aquifers. Here we analyze global groundwater depletion by considering these factors explicitly. Global gridded groundwater availability and extraction cost data are aggregated to produce nonrenewable resource supply curves for 235 major river basins and geopolitical regions. These resources are then exposed to dynamically generated demands for water in a fully coupled, multisectoral, global simulation. As groundwater head levels drop, imposing greater capital and operating costs to bring water to the surface, modeled water use sectors are able to deploy a range of supply‐ and demand‐driven adaptive responses. Results demonstrate large sensitivity in global groundwater depletion rates to adjustments in resource exploitability. Extraction costs moderate demands for nonrenewable water substantially, resulting in the onset of a decline in global groundwater depletion rates within the twenty‐first century. New groundwater depletion hot spots may emerge as crop producers abandon overexploited basins and expand croplands in regions with cheaper, more plentiful water resources.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Frequency-domain Flexibility Characterization of Heterogeneous End-use Loads for Grid Services

Demand response, based on flexible loads, has been a novel and important proposal for smart grids. A population of small loads can be aggregated to provide ancillary services to the grid and generate value for the owners. In this paper, we investigate the flexibility of such populations from the frequency-domain perspective. We propose a methodology to characterize the frequency-dependent flexibility of heterogeneous populations of loads considering practical constraints. The resultant frequency-domain characterization can help flexible load aggregators assess the capability of contracted populations. System operators can also benefit from a better understanding of the capabilities of the service providers. The effectiveness of the methodology is demonstrated by simulations.

Wang, Dexin↗
DOE OSTI2023

Metal–Organic Framework as a New Type of Magnetothermally‐Triggered On‐Demand Release Carrier

The development of external stimuli‐controlled payload systems has been sought after with increasing interest toward magnetothermally‐triggered drug release (MTDR) carriers due to their non‐invasive features. However, current MTDR carriers present several limitations, such as poor heating efficiency caused by the aggregation of iron oxide nanoparticles (IONPs) or the presence of antiferromagnetic phases which affect their efficiency. Herein, a novel MTDR carrier is developed using a controlled encapsulation method that fully fixes and confines IONPs of various sizes within the metal–organic frameworks (MOFs). This novel carrier preserves the MOF's morphology, porosity, and IONP segregation, while enhances heating efficiency through the oxidation of antiferromagnetic phases in IONPs during encapsulation. It also features a magnetothermally‐responsive nanobrush that is stimulated by an alternating magnetic field to enable on‐demand drug release. The novel carrier shows improved heating, which has potential applications as contrast agents and for combined chemo and magnetic hyperthermia therapy. It holds a great promise for magneto‐thermally modulated drug dosing at tumor sites, making it an exciting avenue for cancer treatment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Renewable hydrogen and ammonia for combined heat and power systems in remote locations: Optimal design and scheduling

Abstract Using hydrogen (H ) and ammonia (NH ) for renewable energy storage has the potential to enable economical power and heat supply with high renewable penetrations, especially in remote locations which are characterized by high energy costs. In this work we assess the economic competitiveness of renewable combined heat and power (CHP) systems in Mahaka HI, Nantucket MA, and Northwest Arctic Borough (NWAB) AK by optimally designing these systems for scenarios in which power and heat can be purchased over a range of historical energy prices as well as when 100% renewable supply is required. We use a combined optimal design and scheduling model which minimizes annualized net present cost by determining optimal technology selection and size simultaneously with optimal schedules for each period of a system operating horizon aggregated from full year hourly resolution data via a consecutive temporal clustering algorithm. We find that renewable generation meets at least 85% of power demands and 75% of heat demands under the lowest energy prices investigated. Higher conventional energy prices lead to increased renewable penetration which is facilitated by renewable NH as a seasonal energy storage medium, as are 100% renewable CHP systems. NH is used for power generation with heat cogeneration in all three locations, as well as directly for heating in NWAB. On an annual cost basis, NH ‐enabled 100% renewable CHP is only 3% more expensive in Mahaka and NWAB than systems which can purchase energy at the lowest prices, while it is 15% more expensive in Nantucket.

Palys, Matthew J.↗
DOE OSTI2014

Interfacial Properties and Design of Functional Energy Materials

The vital importance of energy to society continues to demand a relentless pursuit of energy responsive materials that can bridge fundamental chemical structures at the molecular level and achieve improved functionality, such as efficient energy conversion/storage/transmission, over multiple length scales. This demand can potentially be realized by harnessing the power of self-assembly a spontaneous process where molecules or much larger entities form ordered aggregates as a consequence of predominately non-covalent (weak) interactions. Self-assembly is the key to bottom-up design of molecular devices, because the nearly atomic-level control is very difficult to realize in a top-down, e.g., lithographic approach. However, while function (e.g., charge mobility) in simple systems such as single crystals can often be predicted, predicting the function of the great variety of self-assembled molecular architectures is complicated by the lack of understanding and control over nanoscale interactions, mesoscale architectures, and macroscale (long-range) order. To establish a foundation toward delivering practical solutions, it is critical to develop an understanding of the chemical and physical mechanisms responsible for the self-assembly of molecular and hybrid materials on various substrates. Typically molecular self-assembly involves poorly understood non-covalent intermolecular and substrate-molecule interactions compounded by local and/or collective influences from the substrate atomic lattice (symmetry and/or topological features) and electronic structure. Thus, progress towards unraveling the underlying physicochemical processes that control the structure and macroscopic physical, mechanical, electrical, and transport properties of materials increasingly requires tight integration of theory, modeling and simulation with precision synthesis, advanced experimental characterization, and device measurements. In this mode, theory and simulation can greatly accelerate the process of materials discovery by providing atomic level understanding of physicochemical phenomena and for making predictions of trends. In particular, this approach can provide understanding, prediction and exploration of new materials and conditions before they are realized in the lab, to illuminate connections between experimental observations, and help identify new materials for targeted synthesis. Toward this end, Density Functional Theory (DFT) can provide a suitable computational framework for investigating the inter- and intramolecular bonding, molecular conformation, charge and spin configurations that are intrinsic to self-assembly of molecules on substrates. This Account highlights recent advances in using an integrated approach based on DFT and scanning probe microscopy [STM(s), AFM] to study/develop electronic materials formed from the self-assembly of molecules into supramolecular or polymeric architectures on substrates. Here it is the interplay between molecular interactions and surface electrons that is used to control the final architecture and subsequent bulk properties of the two-dimensional patterns/assemblies. Indeed a rich variety of functional energy materials become possible.

Sumpter, Bobby G↗
DOE OSTI2025

Dependent scattering and fractal microstructure determine the transparency of aerogel monoliths

This study reveals how dependent scattering and microstructure significantly affect electromagnetic wave propagation through aerogel monoliths, contributing to their transparency. Light scattering by particle ensembles is considered “dependent” when the scattering properties rely not only on particle size and optical constants but also on their spatial distribution, typically occurring when the average interparticle distance is small in comparison with the wavelength of incident radiation. Addressing dependent scattering requires solving Maxwell’s equations for complex heterogeneous structures, which is computationally demanding and usually limited to sample thicknesses on the same scale as the wavelength. This study combines computer-generated ambigel microstructures of fractal aggregates of polydisperse nanoparticles and the radiative transfer with reciprocal transaction method to predict the transmittance of thick ambigel slabs. Transmittance measurements of ambiently dried aerogel monoliths (ambigels) with porosities from about 50% to 90% closely matched the predicted values for their digital twins. However, ignoring dependent scattering or particle aggregation led to inaccurate predictions. This study validated the computational framework, and its findings offer insights for designing photonic metamaterials and analyzing their interactions with electromagnetic waves.

Yalcin, Refet A. (ORCID:0000000339973494)↗
DOE OSTI2018

A Hierarchical VLSM-Based Demand Response Strategy for Coordinative Voltage Control between Transmission and Distribution Systems

This paper presents a two-stage hierarchical voltage-load sensitivity matrix (VLSM)-based demand response (DR) algorithm for regulating the voltage at distribution feeders while fulfilling the transmission system DR requests. This allows distributed energy resources be aggregated to provide transmission-level services without causing operational issues in the distribution grids. At the beginning of each operation interval, a transmission system controller will issue DR commands to distribution system controllers. In the first stage, the distribution system controller uses a VLSM-based dispatch algorithm to dispatch the available DR resources on the distribution feeder with an objective to minimize the total voltage deviations at the lowest cost. Then, power flow studies are conducted assuming that the DR commands have been executed. If voltage violations are detected, a second-stage VLSM-based DR dispatch will be performed to remove those violations. After that, the upper and lower DR limits calculated for the next operation interval are sent back to the transmission system controller so the transmission optimization algorithm can use them as operational constraints to make subsequent decisions. The DR resources include smart photovoltaic (PV) inverters that can curtail real power and provide reactive power support, controllable loads and capacitor banks. In conclusion, the IEEE 123-bus test system with 5-minute PV and load data is used to evaluate the performance of the algorithm. In conclusion, simulation results show that the proposed algorithm can fulfill the transmission-level DR requests while maintaining the voltage in the distribution system within limits.

24 POWER TRANSMISSION AND DISTRIBUTION↗